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ICMLA
2007
13 years 6 months ago
Improving gene expression programming performance by using differential evolution
Gene Expression Programming (GEP) is an evolutionary algorithm that incorporates both the idea of a simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and...
Qiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Ne...
ACSC
2009
IEEE
13 years 12 months ago
Inference of Gene Expression Networks Using Memetic Gene Expression Programming
In this paper we aim to infer a model of genetic networks from time series data of gene expression profiles by using a new gene expression programming algorithm. Gene expression n...
Armita Zarnegar, Peter Vamplew, Andrew Stranieri
GECCO
2005
Springer
180views Optimization» more  GECCO 2005»
13 years 10 months ago
Inference of gene regulatory networks using s-system and differential evolution
In this work we present an improved evolutionary method for inferring S-system model of genetic networks from the time series data of gene expression. We employed Differential Ev...
Nasimul Noman, Hitoshi Iba
BMCBI
2006
153views more  BMCBI 2006»
13 years 5 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
BMCBI
2010
154views more  BMCBI 2010»
13 years 5 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...